• Water for future
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• v.23 no.3
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• pp.385-395
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• 1990

Three-parameter Muskingum flood routing model which incorporated the inflows alongside the river channel is applied for the Waegwan-Jeukpogyo reach of the Nakdong River using the flood data of 12 selected flood events experienced in this reach. The flood routing equations for three-parameter model were expressed as a system of finite difference equations and the routing constants were directly computed by matrix inversion method. Then, the three parameters, which consist of the storage constants(K), weighting fator(x), and lateral inflow parameter(α), were determined from the computed routing constants. The results of the present study showed that the model can predict with a fair accuracy the flood discharges at the downsteam end of the reach. The parameters K and x were seen as channel parameters which have close relations with the flood magnitude, whereas the lateral inflow parameter was shown to be strongly governed by the rainfall characteristics of the tributary watersheds contributing to the lateral inflows.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.388-388
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• 2019

하도 홍수추적의 방법은 크게 수리학적 방법과 수문학적 방법으로 구분할 수 있다. 수리학적 홍수추적 방법은 정확하지만 대량의 자료가 필요하고 시간이 오래 걸린다. 이와 반대로 수문학적 홍수추적 방법은 정확성은 떨어지지만 소량의 자료만 있으면 되고 시간이 적게 걸린다. 여러 수문학적 홍수추적에 관한 연구들이 있으며 대표적으로 Muskingum 방법이 있다. Muskingum 방법 중 Linear Muskingum Model(LMM)은 방정식의 구조적 한계 때문에 정확한 홍수추적이 어려웠고, 이를 개선하기위하여 Nonlinear Muskingum Model(NLMM), Nonlinear Muskingum Model Incorporation Lateral Flow(NLMM-L) 및 Advanced Nonlinear Muskingum Model Incorporating Lateral Flow(ANLMM-L)이 제안되었다. 본 연구는 수문학적 홍수추적 중 Muskingum 방법의 결과 차이가 어떤 요인으로 인해 발생하는지 검토하였다. 최적화 알고리즘으로 화음탐색법(Harmony Search, HS)을 사용하였으며 LMM, NLMM, NLMM-L 및 ANLMM-L의 매개변수를 산정하였다. 각 방법에 적용 시 HS의 매개변수에 변화를 주어 민감도 분석을 실시하였으며, 분석을 위한 홍수자료는 The Willson Flood data (1947)를 선택하였다. 오차비교방법은 Sum of Squares(SSQ), Root Mean Square Errors(RMSE), Nash-Sutcliffe Efficiency(NSE)를 비교하였다. 비교 결과 알고리즘의 성능에 의한 차이보다 홍수추적 방법의 차이가 더 영향이 큰 것으로 나타났다.

• Journal of Wetlands Research
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• v.18 no.2
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• pp.148-153
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• 2016

Hydraulic and hydrological flood routing methods are commonly used to analyze temporal and spatial flood influences of flood wave through a river reach. Hydrological flood routing method has relatively more simple and reasonable performance accuracy compared to the hydraulic method. Storage constant used in Muskingum method widely applied in hydrological flood routing is very similar to the travel time. Focusing on this point, in this study, we estimate the travel time from HEC-RAS results to estimate storage constant, and develop a non-linear regression equation for the travel time using reach length, channel slope, and discharge. The estimated flow by Muskingum model with storage constant of nonlinear equation is compared with the flow calculated by applying the HEC-RAS 1-D unsteady flow simulation. In addition, this study examines the effect on the weighting factor changes and interval reach divisions; peak discharge increases with the bigger weighting factor, and RMSE decreases with the fragmented division.

• Journal of Korea Water Resources Association
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• v.53 no.8
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• pp.597-604
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• 2020

Muskingum, a hydrologic channel flood routing, is a method of predicting outflow by using the relationship between inflow, outflow, and storage. As many studies for Muskingum model were suggested, parameters were gradually increased and the calculation process was complicated by many parameters. To solve this problem, an optimization algorithm was applied to the parameter estimation of Muskingum model. This study applied the Advanced Nonlinear Muskingum Model considering continuous flow (ANLMM-L) to Wilson flood data and Sutculer flood data and compared results of the Linear Nonsingum Model incorporating Lateral flow (LMM-L), and Kinematic Wave Model (KWM). The Sum of Squares (SSQ) was used as an index for comparing simulated and observed results. Exponential Bandwidth Harmony Search with Centralized Global Search (EBHS-CGS) was applied to the parameter estimation of ANLMM-L. In Wilson flood data, ANLMM-L showed more accurate results than LMM-L. In the Sutculer flood data, ANLMM-L showed better results than KWM, but SSQ was larger than in the case of Wilson flood data because the flow rate of Sutculer flood data is large. EBHS-CGS could be appplied to be appplicable to various water resources engineering problems as well as Muskingum flood routing in this study.

• Water for future
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• v.18 no.3
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• pp.265-270
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• 1985

The prediction of a design-flood hydrograph at a particular site on a river may be based on the derivation of discharge or stage hydrograph at an upstream section, togeater with a method to route this hydrograph along the rest of river. On the other hand, flood routing methods provide a useful tool for the analysis of flooding in all but the smaller catchment, and these methods are largely stored into hydrological method and hydraulic method. Although the Muskingum Method as a hydrological method ignores dynamic effects on the flood wave, Muskingum-Cunge Method based on hydraulic method is possible to improve the method so that it gives a good approximation to the solution of the linear convective-diffusion equation. This is made on the basis of the finite diffeience equation for the Muskingum Method. In the study, the outflows predicted by Muskingum-Cunge Method are campared with the observed outflows of the Pyung Chang River.

• Journal of Korea Water Resources Association
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• v.43 no.12
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• pp.1051-1061
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• 2010

This study hydrologically re-analysed the Muskingum channel routing method to represent it as a linear combination of the linear channel model considering only the translation and the linear reservoir model considering only the storage effect. The resulting model becomes a kind of instantaneous unit hydrograph, whose parameters are identical to those of the Muskingum model. That is, the outflow occurs after the routing interval ${\Delta}t$ or concentration time $T_c$, and among the total amount of inflow, the x portion is translated by the linear channel model and the remaining (1-x) portion is routed by the linear reservoir model with the storage coefficient ��$K_c$. The application result of both the Muskingum channel routing method and its corresponding instantaneous unit hydrograph to an imaginary channel showed that these two models are basically identical. This result was also assured by the application to the channel flood routing to the Kumnam and Gongju Station for the discharge from the Daechung Dam.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.29-37
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• 2020

In the past, meta-heuristic optimization algorithms were developed to solve the problems caused by complex nonlinearities occurring in natural phenomena, and various studies have been conducted to examine the applicability of the developed algorithms. The self-adaptive vision correction algorithm (SAVCA) showed excellent performance in mathematics problems, but it did not apply to complex engineering problems. Therefore, it is necessary to review the application process of the SAVCA. The SAVCA, which was recently developed and showed excellent performance, was applied to the advanced Muskingum flood routing model (ANLMM-L) to examine the application and application process. First, initial solutions were generated by the SAVCA, and the fitness was then calculated by ANLMM-L. The new value selected by a local and global search was put into the SAVCA. A new solution was generated, and ANLMM-L was applied again to calculate the fitness. The final calculation was conducted by comparing and improving the results of the new solution and existing solutions. The sum of squares (SSQ) was used to calculate the error between the observed and calculated runoff, and the applied results were compared with the current models. SAVCA, which showed excellent performance in the Muskingum flood routing model, is expected to show excellent performance in a range of engineering problems.

• Journal of the Korean Society of Industry Convergence
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• v.7 no.3
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• pp.281-288
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• 2004

The objective of this study is to propose a methodology of the flood runoff analysis in steep mountainous basins and the analysis basin is the Jasa valley basin in Chungju city Analyzing the spatial pattern of the rainfall in 1994. 6 30~7.1, the seasonal rainy front was tied up in the whole central district, and the rainfall center was moving from the northern Chungbuk province to the northern Kyongbuk province and caused heavy storm. Analyzing the temporal pattern with the Huff method, the 52.5% of the rainfall was concentrated on the 3rd quartile. Rainfall frequency analysis is accomplished by five distribution types; 2-parameter Lognomal, 3-parameter Lognomal, Pearson Type III, Log-Pearson Type III and Extremal Type I distribution Rainfall-runoff analysis in Jasa valley basin was made using HEC-HMS model. Jasa valley basin was divided into 3 sub-basins and the analysis point was 3 points{A, B and C point) With the rainfall data measured by the 10 minutes, the flood runoff also was calculated by as many minutes. SCS CN model, Clark UH model and Muskingum routing model in HEC-HMS model were used to simulate the runoff volume using selected rainfall event.

• Journal of Korea Water Resources Association
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• v.50 no.12
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• pp.827-836
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• 2017

The most important parameters of the Muskingum method, widely used in hydrologic river routing, are the storage coefficient and the weighting factor. The Muskingum method does not consider the lateral inflow from the upstream to the downstream, but the lateral inflow actually occurs due to the rainfall on the watershed. As a result, it is very difficult to estimate the storage coefficient and the weighting factor by using the actual data of upstream and downstream. In this study, the flow without the lateral inflow was calculated from the river flow through the hydraulic flood routing by using the HEC-RAS one-dimensional unsteady flow model, and the method of the storage coefficient and the weighting factor calculation is presented. Considering that the storage coefficient relates to the travel time, the empirical travel time formulas used in the establishment of the domestic river basin plan were applied as the storage coefficient, and the simulation results were compared and analyzed. Finally, we have developed a formula for calculating the travel time considering the flow rate, and proposed a method to perform flood routing by updating the travel time according to the inflow change. The rise and fall process of the flow rate, the peak flow rate, and the peak time are well simulated when the travel time in consideration of the flow rate is applied as the storage coefficient.

• Journal of Korea Water Resources Association
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• v.42 no.1
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• pp.61-73
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• 2009

To efficiently carry out the flood management of a multipurpose dam, two flood forecasting models are developed, each of which has the capabilities of forecasting upstream inflows and flood discharges downstream of a dam, respectively. The models are calibrated, validated, and evaluated by comparison of the observed and the runoff forecasts upstream and downstream of Namgang Dam. The upstream inflow forecasting model is based on the Grey system theory and employs the sixth order differential equation. By comparing the inflows forecasted by the models calibrated using different data sets with the observed in validation, the most appropriate model is determined. To forecast flood discharges downstream of a dam, a Grey model is integrated with a modified Muskingum flow routing model. A comparison of the observed and the forecasted values in validation reveals that the model can provide good forecasts for the dam's flood management. The applications of the two models to forecasting floods in real situations show that they provide reasonable results. In addition, it is revealed that to enhance the prediction accuracy, the models are necessary to be calibrated and applied considering runoff stages; the rising, peak, and falling stages.